
Pentzold et al. 3
In this respect, Portmess and Tower (2015) claim that the term big data is in itself “a
trove of suggested meanings for semantic exploration” (p. 3). They argue that the meta-
phorical contents of the discourse around the term “carry suggestive implications for
exploring different ways of envisioning our relationship to emerging information tech-
nologies” (p. 3). Likewise, considering big data in historical and political dimensions,
Beer (2016) invites us to see them as “an interweaving of a material phenomenon and
circulating concept” (p. 4). The metaphors around big data do not only shape the collec-
tive mindsets on big data, but also their governance (Hwang and Levy, 2015). “How
what counts as data (and data’s referent) is a social process with political overtones,”
Boellstorff and Maurer (2015: 3) thus postulate.
Against this background, the scant attention to the imagery circulating around big
data is especially conspicuous given the precept that data are abstract. While their abstract
quality makes it difficult to think or write about data in general, “it follows from their
abstraction that data ironically require material expression,” Gitelman and Jackson
(2013: 6) state. So we suppose that journalistic reports require visual displays in order to
envision what big data actually are and what their implications would be for citizens,
commerce, or society writ large (Coleman, 2010; Messaris and Abraham, 2001).
Consequently, our study first asks: What types of images are employed in order to illus-
trate articles on big data (RQ1)?
Overall, this study resonates with analyses of the meaning work around science and
emerging technologies (e.g. Cacciatore et al., 2012; Druckman and Bolsen, 2011). A
chief communicative function of media frames lies in the contextualization of quite
abstract issues, such as nanotechnology or molecular science, by offering patterns of
interpretation. They select and highlight certain aspects and thus predispose understand-
ing and stimulate public action. In this respect, big data might function as a prime motive
for framing strategies too because, as Beer (2016) posits, the very concept of big data
“shapes decisions, judgments and notions of value” (p. 5). Accordingly, the language
around the concept is rich with metaphorical rhetoric that speaks of the “dataverse,”
“data deluge,” “data explosion,” and of big data as the “new oil” (Lupton, 2013, 2014;
Puschmann and Burgess, 2014).
Compared to written texts, visuals are perceived in a holistic and associative manner
and attain superior salience compared to verbal material and, thus, can be highly effec-
tive for articulating ideological messages (Brantner et al., 2013; Messaris and Abraham,
2001). Nevertheless, there are only a few studies on the visual framing of abstract themes
in technology and science, let alone big data. Most of the work that examines the visual
framing of less tangible issues deals with the depiction of climate change (e.g. Rebich-
Hespanha et al., 2015; Wessler et al., 2016). It finds that climate images show identifia-
ble people (most often politicians, but also scientists, citizens, business leaders, and
celebrities), causes of climate change (such as through iconic images of smokestacks),
and the impacts of climate change.
In case the visual dimension is discussed at all, the lack of creativity in depicting big
data is criticized. For example, the Tumblr blog bigdatapix (2017) assembled a collection
of visuals only to conclude that “Big Data is visualized in so many ways … all of them
blue and with numbers and lens flare.” As a case in point, searching for images of “big
data” on Google brings up a visually coherent sample (see Figure 1). We see word clouds,